Senior AI Performance and Efficiency Engineer
AI summary of the role
This role focuses on improving AI/ML research efficiency across NVIDIA's GPU clusters by identifying and resolving infrastructure and application bottlenecks.
What you’ll do
- Collaborate with AI/ML researchers to make ML models more efficient, driving productivity and cost savings
- Build tools, frameworks, and apply ML techniques to detect and analyze efficiency bottlenecks
- Work with researchers on diverse ML workloads including Robotics, Autonomous vehicles, LLMs, and Video
- Proactively monitor fleet-wide utilization patterns and deliver scalable solutions for inefficiencies
What you’ll bring
- BS or equivalent in Computer Science or related field
- 5+ years designing and operating large scale compute infrastructure
- Strong understanding of modern ML techniques and tools
- Experience debugging and optimizing training & inference performance end to end
Technologies
GPU Clusters · NSight Systems · NSight Compute · NCCL · CUDA · InfiniBand · RDMA · Lustre · GPFS · PyTorch · TensorFlow · MLPerf
About NVIDIA
Designs and manufactures GPUs and system-on-chips powering data centers, AI workloads, gaming, autonomous vehicles, and HPC. The foundational hardware for modern deep learning.
Public
Source and classification
Internal deployment & tooling · Evidence for this classification:
We are seeking a Senior AI/ML Performance and Efficiency Engineer, GPU Clusters at NVIDIA to join our AI Efficiency efforts. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure and application deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology! What you will be doing: Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for
More from the job description
We are seeking a Senior AI/ML Performance and Efficiency Engineer, GPU Clusters at NVIDIA to join our AI Efficiency efforts. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure and application deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology! What you will be doing: Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers Work with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM’s, Videos and more Collaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure Proactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them Keep up to date with the most recent developments in AI/ML te [... source excerpt omitted ...] ur location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until March 23, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, nat
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